Experimental investigation and prediction of wear behavior of cotton fiber polyester composites
Abstract The cotton fiber reinforced polyester composites were fabricated with varying amount of graphite fillers (0, 3, 5 wt.%) with a hand lay-up technique. Wear tests were planned by using a response surface (Box Behnken method) design of experiments and conducted on a pin-on-disc machine (POD) t...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2017-05-01
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| Series: | Friction |
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| Online Access: | http://link.springer.com/article/10.1007/s40544-017-0145-y |
| _version_ | 1830341100075745280 |
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| author | Hiral H. Parikh Piyush P. Gohil |
| author_facet | Hiral H. Parikh Piyush P. Gohil |
| author_sort | Hiral H. Parikh |
| collection | DOAJ |
| description | Abstract The cotton fiber reinforced polyester composites were fabricated with varying amount of graphite fillers (0, 3, 5 wt.%) with a hand lay-up technique. Wear tests were planned by using a response surface (Box Behnken method) design of experiments and conducted on a pin-on-disc machine (POD) test setup. The effect of the weight percentage of graphite content on the dry sliding wear behavior of cotton fiber polyester composite (CFPC) was examined by considering the effect of operating parameters like load, speed, and sliding distance. The wear test results showed the inclusion of 5 wt.% of graphite as fillers in CFPC increase wear resistance compared to 3 wt.% of graphite fillers. The graphite fillers were recommended for CFPC to increase the wear resistance of the material. A scanning electron microscope (SEM) was used to study the wear mechanism. To predict the wear behavior of the composite material, comparisons were made between the general regression technique and an artificial neural network (ANN). The conformation test results revealed the predicted wear with the ANN was acceptable when compared with the actual experimental results and the regression mathematical models. |
| first_indexed | 2024-12-19T21:27:17Z |
| format | Article |
| id | doaj.art-35a68a4546ca48a5beb408af86996599 |
| institution | Directory Open Access Journal |
| issn | 2223-7690 2223-7704 |
| language | English |
| last_indexed | 2024-12-19T21:27:17Z |
| publishDate | 2017-05-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Friction |
| spelling | doaj.art-35a68a4546ca48a5beb408af869965992022-12-21T20:05:04ZengSpringerOpenFriction2223-76902223-77042017-05-015218319310.1007/s40544-017-0145-yExperimental investigation and prediction of wear behavior of cotton fiber polyester compositesHiral H. Parikh0Piyush P. Gohil1Department of Mechanical Engineering, School of Science and Engineering, Navrachana UniversityDepartment of Mechanical Engineering, Faculty of Technology & Engineering, the M S University of BarodaAbstract The cotton fiber reinforced polyester composites were fabricated with varying amount of graphite fillers (0, 3, 5 wt.%) with a hand lay-up technique. Wear tests were planned by using a response surface (Box Behnken method) design of experiments and conducted on a pin-on-disc machine (POD) test setup. The effect of the weight percentage of graphite content on the dry sliding wear behavior of cotton fiber polyester composite (CFPC) was examined by considering the effect of operating parameters like load, speed, and sliding distance. The wear test results showed the inclusion of 5 wt.% of graphite as fillers in CFPC increase wear resistance compared to 3 wt.% of graphite fillers. The graphite fillers were recommended for CFPC to increase the wear resistance of the material. A scanning electron microscope (SEM) was used to study the wear mechanism. To predict the wear behavior of the composite material, comparisons were made between the general regression technique and an artificial neural network (ANN). The conformation test results revealed the predicted wear with the ANN was acceptable when compared with the actual experimental results and the regression mathematical models.http://link.springer.com/article/10.1007/s40544-017-0145-ywearcompositescotton fiber reinforced polyester compositesartificial neural networkpin-on-disc |
| spellingShingle | Hiral H. Parikh Piyush P. Gohil Experimental investigation and prediction of wear behavior of cotton fiber polyester composites Friction wear composites cotton fiber reinforced polyester composites artificial neural network pin-on-disc |
| title | Experimental investigation and prediction of wear behavior of cotton fiber polyester composites |
| title_full | Experimental investigation and prediction of wear behavior of cotton fiber polyester composites |
| title_fullStr | Experimental investigation and prediction of wear behavior of cotton fiber polyester composites |
| title_full_unstemmed | Experimental investigation and prediction of wear behavior of cotton fiber polyester composites |
| title_short | Experimental investigation and prediction of wear behavior of cotton fiber polyester composites |
| title_sort | experimental investigation and prediction of wear behavior of cotton fiber polyester composites |
| topic | wear composites cotton fiber reinforced polyester composites artificial neural network pin-on-disc |
| url | http://link.springer.com/article/10.1007/s40544-017-0145-y |
| work_keys_str_mv | AT hiralhparikh experimentalinvestigationandpredictionofwearbehaviorofcottonfiberpolyestercomposites AT piyushpgohil experimentalinvestigationandpredictionofwearbehaviorofcottonfiberpolyestercomposites |